In this paper we introduce data quality mining (DQM) as a new and promising data mining approach from the academic and the business point of view. The goal of DQM is to employ data mining methods in order to detect, quantify, explain and correct data quality deficiencies in very large databases. Data quality is crucial for many applications of knowledge discovery in databases (KDD). So a typica...

Based on the findings of Massachusetts Institute of Technology, organizations’ data double every five years. However, the rate of using data is 0.3. Nowadays, data mining tools have greatly facilitated the process of knowledge extraction from a welter of data. This paper presents a hybrid model using data gathered from an ATM manufacturing company. The steps of the research are based on CRISP-D...

At present, China exists a problem that the cost of food sampling inspection is too high. This paper attempts to reduce number items in same category, inspection, and improve work efficiency through association analysis national data. And this applies Apriori algorithm analyse rules, which based on unqualified pastry data 2019 database. Finally, we obtain 10 strong rules experiments. The result...